Raw Photoplethysmography as an Enhancement for Research-Grade Wearable Activity Monitors.

IF 5.4 2区 医学 Q1 HEALTH CARE SCIENCES & SERVICES
Paul R Hibbing, Maryam Misal Khan
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引用次数: 0

Abstract

Wearable monitors continue to play a critical role in scientific assessments of physical activity. Recently, research-grade monitors have begun providing raw data from photoplethysmography (PPG) alongside standard raw data from inertial sensors (accelerometers and gyroscopes). Raw PPG enables granular and transparent estimation of cardiovascular parameters such as heart rate, thus presenting a valuable alternative to standard PPG methodologies (most of which rely on consumer-grade monitors that provide only coarse output from proprietary algorithms). The implications for physical activity assessment are tremendous, since it is now feasible to monitor granular and concurrent trends in both movement and cardiovascular physiology using a single noninvasive device. However, new users must also be aware of challenges and limitations that accompany the use of raw PPG data. This viewpoint paper therefore orients new users to the opportunities and challenges of raw PPG data by presenting its mechanics, pitfalls, and availability, as well as its parallels and synergies with inertial sensors. This includes discussion of specific applications to the prediction of energy expenditure, activity type, and 24-hour movement behaviors, with an emphasis on areas in which raw PPG data may help resolve known issues with inertial sensing (eg, measurement during cycling activities). We also discuss how the impact of raw PPG data can be maximized through the use of open-source tools when developing and disseminating new methods, similar to current standards for raw accelerometer and gyroscope data. Collectively, our comments show the strong potential of raw PPG data to enhance the use of research-grade wearable activity monitors in science over the coming years.

将原始光敏血压计作为研究级可穿戴活动监测器的增强功能
可穿戴监测仪在体育锻炼的科学评估中继续发挥着至关重要的作用。最近,研究级监测仪开始提供光电血压计(PPG)的原始数据以及惯性传感器(加速度计和陀螺仪)的标准原始数据。原始 PPG 可以对心率等心血管参数进行精细、透明的估算,因此是标准 PPG 方法(其中大部分依赖于只能提供专有算法粗略输出的消费级监护仪)的重要替代品。这对体力活动评估的影响是巨大的,因为现在只需使用一台无创设备,就能同时监测运动和心血管生理的细微变化趋势。不过,新用户也必须了解使用原始 PPG 数据所面临的挑战和限制。因此,本观点文件通过介绍原始 PPG 数据的力学原理、隐患、可用性及其与惯性传感器的相似性和协同性,让新用户了解原始 PPG 数据带来的机遇和挑战。这包括讨论能量消耗、活动类型和 24 小时运动行为预测的具体应用,重点是原始 PPG 数据可能有助于解决惯性传感已知问题的领域(例如,骑自行车活动期间的测量)。我们还讨论了在开发和传播新方法时,如何通过使用开源工具(类似于当前的原始加速度计和陀螺仪数据标准)最大限度地发挥原始 PPG 数据的影响。总之,我们的评论表明,原始 PPG 数据具有强大的潜力,可在未来几年内提高科研级可穿戴活动监测器在科学领域的应用。
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来源期刊
JMIR mHealth and uHealth
JMIR mHealth and uHealth Medicine-Health Informatics
CiteScore
12.60
自引率
4.00%
发文量
159
审稿时长
10 weeks
期刊介绍: JMIR mHealth and uHealth (JMU, ISSN 2291-5222) is a spin-off journal of JMIR, the leading eHealth journal (Impact Factor 2016: 5.175). JMIR mHealth and uHealth is indexed in PubMed, PubMed Central, and Science Citation Index Expanded (SCIE), and in June 2017 received a stunning inaugural Impact Factor of 4.636. The journal focusses on health and biomedical applications in mobile and tablet computing, pervasive and ubiquitous computing, wearable computing and domotics. JMIR mHealth and uHealth publishes since 2013 and was the first mhealth journal in Pubmed. It publishes even faster and has a broader scope with including papers which are more technical or more formative/developmental than what would be published in the Journal of Medical Internet Research.
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